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| (105) | In general, the probative value of statistical evidence depends on its ability to avoid the risk of so-called type 1 errors, i.e. finding a passing-on effect when none actually exists, and so-called type 2 errors, i.e. failing to find a passing-on effect where there actually is one. In order to deal with these risks, a statistical model may apply the concepts of statistical significance and statistical power. The concept of statistical significance involves setting a high bar for a passing-on effect to be considered existing. An approach widely used is to set a five percent risk for a type 1 error, using a so-called 95 percent confidence interval (91). However, regression models may also reduce the risk of type 2 errors (92). In a specific case where passing-on is estimated, it is for the court to decide whether a regression-model, that has been presented to it, avoids the risks of type 1 and type 2 errors to such an extent that the model has probative value.

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Source: EUR-Lex (Cellar) · retrieved 2026-09-25 · Text as adopted (Official Journal); later amendments are not incorporated in this text.